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HUMAN doctoral network

Multidisciplinary consortium

To put together a multidisciplinary consortium with the critical mass to address the limitations in human LC-MS based blood metabolomics, such as result reproducibility and research fragmentation.
Cross-laboratory comparisons

To perform cross-laboratory comparisons to identify the sources of variability in all steps of metabolomics studies: preanalytical, sample preparation, LC-MS analysis, data quality assessment, normalization, statistical processing, pathway analysis and biochemical interpretation. Understanding and solving these issues will lead to improved comparability of results among labs.
Integration and co-evaluation

To promote the field towards effective integration and co-evaluation of data collected by various labs, improving consistency of findings, data reporting, implementation within databases, reproducibility and re-usability of data. Identify bottlenecks in the integration of metabolomics data (pan-cohorts).
Novel blood microsampling techniques

To investigate the implementation of novel blood microsampling techniques in clinical metabolomics and establish workflows for meaningful blood microsample analysis in biomarker discovery and health monitoring.
Proofing

To provide proof of concept on the utility of the developed tools.